A comparison of Argo nominal surface and near-surface temperature for validation of AMSR-E SST

Zenghong Liu; Xingrong Chen; Chaohui Sun; Xiaofen Wu; Shaolei Lu

doi:10.1007/s00343-017-5330-3

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A comparison of Argo nominal surface and near-surface temperature for validation of AMSR-E SST

Updated：2023-05-16

- A comparison of Argo nominal surface and near-surface temperature for validation of AMSR-E SST
- Journal of Oceanology and Limnology Vol. 35, Issue 3, Pages: 712-721(2017)
- Affiliations：
  
  1. State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of Oceanography State Oceanic Administration
  2. Second Institute of Oceanography State Oceanic Administration
  3. National Marine Environmental Forecasting Center
- Author bio：
- Funds：
- DOI：10.1007/s00343-017-5330-3
  CLC：
- Online First：29 June 2016，
  
  Published：2017
- Accepted：
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Liu, Z., Chen, X., Sun, C. et al. A comparison of Argo nominal surface and near-surface temperature for validation of AMSR-E SST., Chin. J. Ocean. Limnol. 35, 712–721 (2017). https://doi.org/10.1007/s00343-017-5330-3
DOI：

Liu, Z., Chen, X., Sun, C. et al. A comparison of Argo nominal surface and near-surface temperature for validation of AMSR-E SST., Chin. J. Ocean. Limnol. 35, 712–721 (2017). https://doi.org/10.1007/s00343-017-5330-3 DOI：

摘要

Abstract

Satellite SST (sea surface temperature) from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) is compared with in situ temperature observations from Argo profiling floats over the global oceans to evaluate the advantages of Argo NST (near-surface temperature: water temperature less than 1 m from the surface). By comparing Argo nominal surface temperature (~5 m) with its NST

a diurnal cycle caused by daytime warming and nighttime cooling was found

along with a maximum warming of 0.08±0.36°C during 14:00–15:00 local time. Further comparisons between Argo 5-m temperature/Argo NST and AMSR-E SST retrievals related to wind speed

columnar water vapor

and columnar cloud water indicate warming biases at low wind speed (<5 m/s) and columnar water vapor >28 mm during daytime. The warming tendency is more remarkable for AMSR-E SST/Argo 5-m temperature compared with AMSR-E SST/Argo NST

owing to the effect of diurnal warming. This effect of diurnal warming events should be excluded before validation for microwave SST retrievals. Both AMSR-E nighttime SST/Argo 5-m temperature and nighttime SST/Argo NST show generally good agreement

independent of wind speed and columnar water vapor. From our analysis

Argo NST data demonstrated their advantages for validation of satellite-retrieved SST.

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references

Bhat G S, Veechi G A, Gadgil S. 2004. Sea surface temperature of the Bay of Bengal derived from the TRMM Microwave Imager. J. Atmos. Ocean. Tech., 21 (8): 283–1290.

Brown O B, Brown J W, Evans R H. 1985. Calibration of advanced very high resolution radiometer infrared observations. J. Geophys. Res., 90 (6): 1667–11677.

Castro S L, Wick G A, Jackson D L, Emery W J. 2008. Error characterization of infrared and microwave satellite sea surface temperature products for merging and analysis. J. Geophys. Res., 113 (C3): C03010, http://dx.doi.org/10.1029/2006JC003829.

Chen D K, Cane M A. 2008. El Niño prediction and predictability. J. Comput. Phys., 227 (7): 625–3640.

Dong S F, Gille S T, Sprintall J et al. 2006. Validation of the advanced microwave scanning radiometer for the earth observing system (AMSR-E) sea surface temperature in the Southern Ocean. J. Geophys. Res., 111 (C4): C04002, http://dx.doi.org/10.1029/2005JC002934.

Donlon C J, GHRSST-PP Science Team. 2005. The GHRSSTPP product user manual, GDS-v1.5 report. International GHRSST-PP Project Office, Exeter, UK.

Donlon C J, Minnett P J, Gentemann C, Nightingale T J, Barton I J, Ward B, Murray M J. 2002. Toward improved validation of satellite sea surface skin temperature measurements for climate research. J. Clim., 15 (4): 53–369.

Emery W J, Brandt P, Funk A, Böning C. 2006. A comparison of sea surface temperatures from microwave remote sensing of the Labrador Sea with in situ measurements and model simulations. J. Geophys. Res., 111 (C12): C12013, http://dx.doi.org/10.1029/2006JC003578.

Emery W J, Yu Y Y, Wick G A, Schluessel P, Reynolds R W. 1994. Correcting infrared satellite estimates of sea surface temperature for atmospheric water vapor attenuation. J. Geophys. Res., 99 (C3): 5219–5236.

Fairall C W, Bradley E F, Rogers D P, Edson J B, Young G S. 1996. Bulk parameterization of air-sea fluxes for tropical ocean-global atmosphere coupled-ocean atmosphere response experiment. J. Geophys. Res., 101 (C2): 3747–3764.

Flament P, Firing J, Sawyer M, Trefois C. 1994. Amplitude and horizontal structure of a large diurnal sea surface warming event during the Coastal Ocean Dynamics Experiment. J. Phys. Ocean ogr., 24 (1): 24–139.

Gentemann C L, Donlon C J, Stuart-Menteth A, Wentz F J. 2003. Diurnal signals in satellite sea surface temperature measurements. Geophys. Res. Lett., 30 (3): 1140, http://dx.doi.org/10.1029/2002GL016291.

Gentemann C L, Minnett P J, Le Borgne P, Merchant C J. 2008. Multi-satellite measurements of large diurnal warming events. Geophys. Res. Lett., 35 (22): L22602, http://dx.doi.org/10.1029/2008GL035730.

Gentemann C L, Minnett P J, Ward B. 2009. Profiles of ocean surface heating (POSH): a new model of upper ocean diurnal warming. J. Geophys. Res., 114 (C7): C07017, http://dx.doi.org/10.1029/2008JC004825.

Gentemann C L, Minnett P J. 2008. Radiometric measurements of ocean surface thermal variability. J. Geophys. Res., 113 (C8): C08017, http://dx.doi.org/10.1029/2007JC004540.

Gentemann C L, Wentz F J, Mears C A, Smith D K. 2004. In situ validation of Tropical Rainfall Measuring Mission microwave sea surface temperatures. J. Geophys. Res., 109 (C4): C04021, http://dx.doi.org/10.1029/2003JC002092.

Gentemann C L. 2014. Three way validation of MODIS and AMSR-E sea surface temperatures. J. Geophys. Res., 119 (4): 583–2598, http://dx.doi.org/10.1002/2013JC009716.

Gille S T. 2012. Diurnal variability of upper ocean temperatures from microwave satellite measurements and Argo profiles. J. Geophys. Res., 117 (C11): C11027, http://dx.doi.org/10.1029/2012JC007883.

Gohil B S, Mathur A K, Pandey P C. 1994. An algorithm for sea surface temperature estimation from ERS-1 ATSR using moisture dependent coefficients: a simulation study. Int. J. Remote Sens., 15 (5): 161–1167.

Kawai Y, Wada A. 2007. Diurnal sea surface temperature variation and its impact on the atmosphere and ocean: a review. J. Oceanogr., 63 (5): 21–744.

Larson N L, Janzen C D, Murphy D J. 2008. STS: an instrument for extending ARGO temperature and salinity measurements through the sea surface. In: Poster Presented at the 2008 Ocean Sciences Meeting. Orlando, Florida.

McClain E P. 1989. Global sea surface temperatures and cloud clearing for aerosol optical depth estimates. Int. J. Remote Sens., 10(4): 763–769.

McPhaden M J. 1999. Genesis and evolution of the 1997-98 El Niño. Sci ence, 283 (5404): 50–954, http://dx.doi.org/10.1126/science.283.5404.950.

Merchant C J, Filipiak M J, Le Borgne P, Roquet H, Autret E, Piollé J F, Lavender S. 2008. Diurnal warm-layer events in the western mediterranean and european shelf seas. Geophys. Res. Lett., 35 (4): L04601, http://dx.doi.org/10. 1029/2007GL033071.

Minnett P J. 2003. Radiometric measurements of the seasurface skin temperature: the competing roles of the diurnal thermocline and the cool skin. Int. J. Remote Sens., 24 (24): 033–5047.

Muraleedharan P M, Pankajakshan T, Harikrishnan M. 2004. Validation of multi-channel scanning microwave radiometer on-board Oceansat-I. Curr. Sci., 87 (3): 70–376.

Pandey P C, Kniffen S. 1991. Linear retrieval, validation and mapping of the sea surface temperature over western midlatitude North Pacific using Seasat SMMR data. Int. J. Remote Sens., 12 (12): 493–2511.

Parekh A, Sharma R, Sarkar A. 2007. A comparative assessment of surface wind speed and sea surface temperature over the Indian Ocean by TMI, MSMR, and ERA-40. J. Atmos. Ocean. Tech., 24 (6): 131–1142.

Price J F, Weller R A, Pinkel R. 1986. Diurnal cycling: observations and models of the upper ocean response to diurnal heating, cooling, and wind mixing. J. Geophys. Res., 91 (C7): 8411–8427.

Soloviev A, Lukas R. 1997. Observation of large diurnal warming events in the near-surface layer of the western equatorial Pacific warm pool. Deep Sea Res. Part I, 44 (6): 055–1076.

Stramma L, Cornillon P, Weller R A, Price J F, Briscoe M G. 1986. Large diurnal sea surface temperature variability: satellite and in situ measurements. J. Phys. Oceanogr., 16 (5): 27–837.

Suarez M J, Schopf P S. 1988. A delayed action oscillator for ENSO. J. Atmos. Sci., 45 (21): 283–3287.

Udaya Bhaskar T V S, Rahman S H, Pavan I D, Ravichandran M, Nayak S. 2009. Comparison of AMSR-E and TMI sea surface temperature with Argo near-surface temperature over the Indian Ocean. Int. J. Remote Sens., 30 (10): 669–2684.

Wang C Z, Weisberg R H. 2000. The 1997-98 El Niño Evolution Relative to Previous El Niño Events. J. Clim., 13 (2): 88–501.

Wentz F J, Gentemann C, Smith D, Chelton D. 2000. Satellite measurements of sea surface temperature through clouds. Science, 288 (5467): 47–850.

Wentz F J, Gentemann J C, Ashcroft P. 2003. On-orbit calibration of AMSR-E and the retrieval of ocean products. In: Paper presented at 12 th Conference on Satellite Meteorology and Oceanography. American Meteorological Society, Long Beach, CA.

Wentz F J, Meissner T. 1999. AMSR ocean algorithm, version 2. RSS Technical Report 121599A. Remote Sensing Systems, Santa Rosa, Calif.

Wentz F J, Meissner T. 2000. AMSR ocean algorithm, version 2. Report Number 121599A-1. Remote Sensing Systems, Santa Rosa, CA.

Wentz F J. 1996. AMSR ocean algorithm, RSS Technical Report 120296. Remote Sensing System, Santa Rosa, CA.

Wentz F J. 1998. Algorithm theoretical basis document: AMSR ocean algorithm. RSS Technical Report 050198. Remote Sensing System, Santa Rosa, CA.

Yokoyama R, Tanba S, Souma T. 1995. Sea surface effects on the sea surface temperature estimation by remote sensing. Int. J. Remote Sens., 16 (2): 27–238.

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